abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Derive explicit evaluation criteria from the research objective and candidate set.
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Derive explicit evaluation criteria from the research objective and candidate set.
name: define-criteria description: "Derive explicit evaluation criteria from the research objective and candidate set."
Derive explicit evaluation criteria from the research objective and candidate set.
required: [research_objective, candidate_set, decision_context] optional: [stakeholder_priorities, measurement_constraints, candidate_domains] constraints: [criteria must be mutually interpretable across candidates]
1. Extract desired outcomes and constraints from the objective. 2. Translate them into candidate-discriminating criteria with definitions and units. 3. Check completeness, overlap, direction, and measurability. 4. Return the criterion schema and unresolved measurement questions.
produces: [criterion_schema, measurement_definitions, direction_labels, coverage_notes] delta_fields: [findings, open_questions, uncertainties]
Caller supplies objective schema, candidate schema, criterion count bounds, measurement units, direction vocabulary, and overlap policy.
Reject vague criteria lacking an observable measurement or criteria that cannot distinguish any candidate.
| source | criterion | |---|---| | criterion-definition | Criteria count is between 3-12. | | criterion-definition | Each criterion includes name, definition, unit of measurement, and direction (higher-is-better/lower-is-better). | | convergence-scoring-matrix-construction | Normalization method matches the aggregation method. | | convergence-scoring-matrix-construction | Sensitivity testing perturbs at least 3 weight parameters by +/-10%. |
The complete research orchestration system for AI-native science. What It Does Design Philosophy Architecture (v3.2.2) Quick Start Configuration Roadmap License DARE is not a tool that helps you do research. It is the researcher.
Repo: yogsoth-ai/de-anthropocentric-research-engine
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Evaluate competing arguments against stated criteria and produce a reasoned verdict with uncertainty.
Move a scientific object up/down in abstraction or narrow/broaden selected scope dimensions (population, mechanism, context, outcome, timeframe, system…
Run structured attack/defense/adjudication over a claim, candidate, criterion set, or current winner. Perspective, target, escalation depth,…
Aggregate criterion or comparison results into an ordered recommendation under an explicit rule.
Abstract relational structure from source domains, map it to the target, validate depth, and instantiate transferable mechanisms.